Now, from a Silicon Valley hero and bestselling technology writer comes a pointed critique of the hype surrounding computers and their real benefits, especially in education. In High-Tech Heretic, Clifford Stoll questions the relentless drumbeat for "computer literacy" by educators and the computer industry, particularly since most people just use computers for word processing and games--and computers become outmoded or obsolete much sooner than new textbooks or a good teacher.As one who loves computers as much as he disdains the inflated promises made on their behalf, Stoll offers a commonsense look at how we can make a technological world better suited for people, instead of making people better suited to using machines.

    The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

    Practical Algebra is an easy andfun-to-use workout program that quickly puts you in command of allthe basic concepts and tools of algebra. With the aid of practical, real-life examples and applications, you'll learn: * The basic approach and application of algebra to problemsolving * The number system (in a much broader way than you have known itfrom arithmetic) * Monomials and polynomials; factoring algebraic expressions; howto handle algebraic fractions; exponents, roots, and radicals;linear and fractional equations * Functions and graphs; quadratic equations; inequalities; ratio, proportion, and variation; how to solve word problems, andmore Authors Peter Selby and Steve Slavin emphasize practical algebrathroughout by providing you with techniques for solving problems ina wide range of disciplines--from engineering, biology, chemistry, and the physical sciences, to psychology and even sociology andbusiness administration. Step by step, Practical Algebra shows youhow to solve algebraic problems in each of these areas, then allowsyou to tackle similar problems on your own, at your own pace.Self-tests are provided at the end of each chapter so you canmeasure your mastery.

    Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package—PMTK (probabilistic modeling toolkit)—that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

    In the highly litigated area of Special Education, it is imperative that professionals in the field understand the legal requirements of providing a free appropriate public education to students with disabilities. This text presents the necessary information for educators to understand the history and development of special education laws and the requirements of these laws. It provides the reader with the necessary skills to locate pertinent information in law libraries, on the Internet, and other sources to keep abreast of the constant changes and developments in the field. The second edition of The Law and Special Education, one of the top special education law books in the field, includes new information on the Individuals with Disabilities Education Act of 2004 and the No Child Left Behind Act of 2001. It has been updated with the latest information on the statutes, regulations, policy guidance, and cases on special education law.

    But despite universal acceptance of reading's vital importance, the reading gap in our classroom remains, and it is linked to an array of factors, such as parental wealth, education and book ownership, as well as classroom practice. To close this gap, we need to ensure that every teacher has the knowledge and skill to teach reading with confidence.In Closing the Reading Gap, Alex Quigley explores the intriguing history and science of reading, synthesising the debates and presenting a wealth of usable evidence about how children develop most efficiently as successful readers. Offering practical strategies for teachers at every phase of their teaching career, as well as tackling issues such as dyslexia and the role of technology, the book helps teachers to be an expert in how pupils 'learn to read' as well as how they 'read to learn' and explores how reading is vital for unlocking a challenging academic curriculum for every student.With a focus on nurturing pupils' will and skill to read for pleasure and purpose, this essential volume provides practical solutions to help all teachers create a rich reading culture that will enable every student to thrive in school and far beyond the school gates.

    We give you step-by-step instructions on how to do things that you won’t find anywhere else.In over 30 articles and over 18,000 words, this guidebook covers...Maximizing Battery LifeUsing the Camera for Taking Pictures and VideoReplacing the CarouselUsing Text-to-Speech for BooksParental Controls and Preventing Unintentional PurchasesSending free text messagesSetting up and using 4G LTE Wireless InternetSideloading apps and booksOrganizing your books into foldersSetting up EmailSending Documents to the Fire HDX...and much more! Don't miss out on your best chance to master your new Kindle Fire HDX!

    

    Fishing, swimming, golf, tennis. Seems like the ideal location for a former secret agent posing as a retired police officer and part-time private investigator. Until people start disappearing. Suggested reading order for the Nicholas Colt series: COLT LADY 52 POCKET-47 CROSSCUT SNUFF TAG 9 KEY DEATH BLOOD TATTOO SYCAMORE BLUFF THE JACK REACHER FILES: FUGITIVE THE JACK REACHER FILES: VELOCITY (Novella) THE BLOOD NOTEBOOKS Note: Although published at a later date, the events in COLT and LADY 52 precede those in Jude Hardin's debut thriller POCKET-47. All of the books listed work as stand-alone thrillers, depending on reader preference. Nicholas Colt also appears in several short stories, including the one titled RATTLED and the one titled RACKED. Praise for Jude Hardin’s Thrillers: POCKET-47 sucked me in and held me enthralled. Author Jude Hardin keeps the pace frantic, the thrills non-stop, but best of all is his hero, the wonderfully ironic Nicholas Colt. This is a character I'm eager to follow through many adventures to come. —Tess Gerritsen, New York Times bestselling author of ICE COLD. The best PI debut I've read in years, fit to share shelf space with the best of Ross Macdonald, Sue Grafton, and Robert B. Parker. POCKET-47 is so hot you may burn your hands reading. Highly recommended. —J.A. Konrath, author of the Jack Daniels mysteries Hardin gets everything right in his powerhouse thriller debut, which introduces rock star–turned–PI Nicholas Colt. —Publishers Weekly on POCKET-47 KEY DEATH is an exhilarating thriller that punches way above its weight. It hits you hard and fast with crackling suspense, hair-raising twists and stunning revelations. Word of advice: don't start on this one unless you're prepared to stay up all night. —John Ling, author of THE BLASPHEMER Colt is a physical, no-holds-barred PI, reminiscent of Robert B. Parker's Spenser and Lee Child's Jack Reacher, and his debut is action-packed. With a hefty toll of dead bodies, some described in cringe-inducing detail, this is crime fiction at its rawest. Hard-boiled connoisseurs should make Colt's acquaintance now. —Booklist on POCKET-47 With CROSSCUT, Jude Hardin takes the PI novel and psychological suspense to a new, unrestrained level. Fast, fierce, and relentless. —David Morrell, New York Times bestselling creator of Rambo

    Join 39 contributors as they explain how they developed simple and elegant solutions on projects ranging from the Mars lander to a Radiohead video.With Beautiful Data, you will: Explore the opportunities and challenges involved in working with the vast number of datasets made available by the Web Learn how to visualize trends in urban crime, using maps and data mashups Discover the challenges of designing a data processing system that works within the constraints of space travel Learn how crowdsourcing and transparency have combined to advance the state of drug research Understand how new data can automatically trigger alerts when it matches or overlaps pre-existing data Learn about the massive infrastructure required to create, capture, and process DNA data That's only small sample of what you'll find in Beautiful Data. For anyone who handles data, this is a truly fascinating book. Contributors include:Nathan Yau Jonathan Follett and Matt Holm J.M. Hughes Raghu Ramakrishnan, Brian Cooper, and Utkarsh Srivastava Jeff Hammerbacher Jason Dykes and Jo Wood Jeff Jonas and Lisa Sokol Jud Valeski Alon Halevy and Jayant Madhavan Aaron Koblin with Valdean Klump Michal Migurski Jeff Heer Coco Krumme Peter Norvig Matt Wood and Ben Blackburne Jean-Claude Bradley, Rajarshi Guha, Andrew Lang, Pierre Lindenbaum, Cameron Neylon, Antony Williams, and Egon Willighagen Lukas Biewald and Brendan O'Connor Hadley Wickham, Deborah Swayne, and David Poole Andrew Gelman, Jonathan P. Kastellec, and Yair Ghitza Toby Segaran

    

    In Finding and Funding Great Deals, seasoned real estate agent and investor Anson Young guides you through his tried and true methods for finding deals in any market. Inside, he outlines his own methods as well as other techniques to help new and seasoned investors alike improve their real estate business. This is not a magic pill that will turn you in to a successful investor overnight; instead this is a practical guide to several approaches to use in each step of your real estate deal finding journey. Hard work required (but not included with the purchase of this book). Inside, you will learn: Inside, you’ll discover: Marketing methods Several analysis techniques Funding approaches How to help others through pain points Negotiation techniques How to build your business so you can do it all over again.

    The text integrates the new with the old, simplifying explanations, shortening sentences, and improving readability. Hundreds of illustrations cover new developments, espeially those relating to the foreign automotive industry and federal laws governing automotive air pollution, safety, and fuel economy. The Tenth Edition contains two four-color illustrated sections. Many chapters end with vocabulary words and "think-type" review questions, in addition to the National Institute of Automotive Service Excellence (ASE) style of multiple-choice questions. For schools seeking program certification by the national Automotive Technicians Education Foundation (NATEF), the high-priority items from their diagnosis, service, and repair task lists have been included.

    As a result, many students talk about college in ways that cause them to overlook some of their most important learning opportunities. Becoming a Learner asks students to carefully reconsider conventional common sense about college and learning, and invites them to consider a new conversation about college and learning that focuses on who they are becoming and their ability to learn.

    This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results